Scaling Nonparametric Bayesian Inference via Subsample-Annealing

We describe an adaptation of the simulated annealing algorithm to nonparametric clustering and related probabilistic models. This new algorithm learns nonparametric latent structure over a growing and constantly churning subsample of training data, where the portion of data subsampled can be interpreted as the inverse temperature beta(t) in an annealing schedule. Gibbs sampling at high temperature (i.e., with a very small subsample) can more quickly explore sketches of the final latent state by (a) making longer jumps around latent space (as in block Gibbs) and (b) lowering energy barriers (as in simulated annealing). We prove subsample annealing speeds up mixing time N^2 -> N in a simple clustering model and exp(N) -> N in another class of models, where N is data size. Empirically subsample-annealing outperforms naive Gibbs sampling in accuracy-per-wallclock time, and can scale to larger datasets and deeper hierarchical models. We demonstrate improved inference on million-row subsamples of US Census data and network log data and a 307-row hospital rating dataset, using a Pitman-Yor generalization of the Cross Categorization model.Comment: To appear in AISTATS 201

Multi-Agent Deployment for Visibility Coverage in Polygonal Environments with Holes

This article presents a distributed algorithm for a group of robotic agents with omnidirectional vision to deploy into nonconvex polygonal environments with holes. Agents begin deployment from a common point, possess no prior knowledge of the environment, and operate only under line-of-sight sensing and communication. The objective of the deployment is for the agents to achieve full visibility coverage of the environment while maintaining line-of-sight connectivity with each other. This is achieved by incrementally partitioning the environment into distinct regions, each completely visible from some agent. Proofs are given of (i) convergence, (ii) upper bounds on the time and number of agents required, and (iii) bounds on the memory and communication complexity. Simulation results and description of robust extensions are also included

Towards Mott design by δ\delta-doping of strongly correlated titanates

Doping the distorted-perovskite Mott insulators LaTiO$_3$ and GdTiO$_3$ with a single SrO layer along the [001] direction gives rise to a rich correlated electronic structure. A realistic superlattice study by means of the charge self-consistent combination of density functional theory with dynamical mean-field theory reveals layer- and temperature-dependent multi-orbital metal-insulator transitions. An orbital-selective metallic layer at the interface dissolves via an orbital-polarized doped-Mott state into an orbital-ordered insulating regime beyond the two conducting TiO$_2$ layers. We find large differences in the scattering behavior within the latter. Breaking the spin symmetry in $\delta$-doped GdTiO$_3$ results in blocks of ferromagnetic itinerant and ferromagnetic Mott-insulating layers which are coupled antiferromagnetically.Comment: 17 pages, 9 figures, final versio

Billiard knots in a cylinder

We define cylinder knots as billiard knots in a cylinder. We present a necessary condition for cylinder knots: after dividing cylinder knots by possible rotational symmetries we obtain ribbon knots. We obtain an upper bound for the number of cylinder knots with two fixed parameters (out of three). In addition we prove that rosette knots are cylinder knots.Comment: 14 pages, 10 figures, to appear in the Journal of Knot Theor

Methods used in cross-culturalcomparisons of vasomotor symptoms and their determinants

Methodological differences among studies of vasomotor symptoms limit rigorous comparison or systematic review. Vasomotor symptoms generally include hot flushes and night sweats although other associated symptoms exist. Prevalence rates vary between and within populations, but different studies collect data on frequency, bothersomeness, and/or severity using different outcome measures and scales, making comparisons difficult. We reviewed only cross-cultural studies of menopausal symptoms that explicitly examined symptoms in general populations of women in different countries or different ethnic groups in the same country. This resulted in the inclusion of nine studies: Australian/Japanese Midlife Women's Health Study (AJMWHS), Decisions At Menopause Study (DAMeS), Four Major Ethnic Groups (FMEG), Hilo Women's Health Survey (HWHS), Mid-Aged Health in Women from the Indian Subcontinent (MAHWIS), Penn Ovarian Aging Study (POAS), Study of Women's Health Across the Nation (SWAN), Women's Health in Midlife National Study (WHiMNS), and Women's International Study of Health and Sexuality (WISHeS). These studies highlight the methodological challenges involved in conducting multi-population studies, particularly when languages differ, but also highlight the importance of performing multivariate and factor analyses. Significant cultural differences in one or more vasomotor symptoms were observed in 8 of 9 studies, and symptoms were influenced by the following determinants: menopausal status, hormones (and variance), age (or actually, the square of age, age2), BMI, depression, anxiety, poor physical health, perceived stress, lifestyle factors (hormone therapy use, smoking and exposure to passive smoke), and acculturation (in immigrant populations). Recommendations are made to improve methodological rigor and facilitate comparisons in future cross-cultural menopause studies

N-terminal modification of proteins with o-aminophenols.

The synthetic modification of proteins plays an important role in chemical biology and biomaterials science. These fields provide a constant need for chemical tools that can introduce new functionality in specific locations on protein surfaces. In this work, an oxidative strategy is demonstrated for the efficient modification of N-terminal residues on peptides and N-terminal proline residues on proteins. The strategy uses o-aminophenols or o-catechols that are oxidized to active coupling species in situ using potassium ferricyanide. Peptide screening results have revealed that many N-terminal amino acids can participate in this reaction, and that proline residues are particularly reactive. When applied to protein substrates, the reaction shows a stronger requirement for the proline group. Key advantages of the reaction include its fast second-order kinetics and ability to achieve site-selective modification in a single step using low concentrations of reagent. Although free cysteines are also modified by the coupling reaction, they can be protected through disulfide formation and then liberated after N-terminal coupling is complete. This allows access to doubly functionalized bioconjugates that can be difficult to access using other methods

Association of Clinical Characteristics With Variation in Emergency Physician Preferences for Patients.

Importance:Much of the wide variation in health care has been associated with practice variation among physicians. Physicians choosing to see patients with more (or fewer) care needs could also produce variations in care observed across physicians. Objective:To quantify emergency physician preferences by measuring nonrandom variations in patients they choose to see. Design, Setting, and Participants:This cross-sectional study used a large, detailed clinical data set from an electronic health record system of a single academic hospital. The data set included all emergency department (ED) encounters of adult patients from January 1, 2010, to May 31, 2015, as well as ED visits information. Data were analyzed from September 1, 2018, to March 31, 2019. Exposure:Patient assignment to a particular emergency physician. Main Outcomes and Measures:Variation in patient characteristics (age, sex, acuity [Emergency Severity Index score], and comorbidities) seen by emergency physicians before patient selection, adjusted for temporal factors (seasonal, weekly, and hourly variation in patient mix). Results:This study analyzed 294 915 visits to the ED seen by 62 attending physicians. Of the 294 915 patients seen, the mean (SD) age was 48.6 (19.8) years and 176 690 patients (59.9%) were women. Many patient characteristics, such as age (F = 2.2; P < .001), comorbidities (F = 1.7; P < .001), and acuity (F = 4.7; P < .001), varied statistically significantly. Compared with the lowest-quintile physicians for each respective characteristic, the highest-quintile physicians saw patients who were older (mean age, 47.9 [95% CI, 47.8-48.1] vs 49.7 [95% CI, 49.5-49.9] years, respectively; difference, +1.8 years; 95% CI, 1.5-2.0 years) and sicker (mean comorbidity score: 0.4 [95% CI, 0.3-0.5] vs 1.8 [95% CI, 1.7-1.8], respectively; difference, +1.3; 95% CI, 1.2-1.4). These differences were absent or highly attenuated during overnight shifts, when only 1 physician was on duty and there was limited room for patient selection. Compared with earlier in the shift, the same physician later in the shift saw patients who were younger (mean age, 49.7 [95% CI, 49.4-49.7] vs 44.6 [95 % CI, 44.3-44.9] years, respectively; difference, -5.1 years; 95% CI, 4.8-5.5) and less sick (mean comorbidity score: 0.7 [95% CI, 0.7-0.8] vs 1.1 [95% CI, 1.1-1.1], respectively; difference, -0.4; 95% CI, 0.4-0.4). Accounting for preference variation resulted in substantial reordering of physician ranking by care intensity, as measured by ED charges, with 48 of 62 physicians (77%) being reclassified into a different quintile and 9 of 12 physicians (75%) in the highest care intensity quintile moving into a lower quintile. A regression model demonstrated that 22% of reported ED charges were associated with physician preference. Conclusions and Relevance:This study found preference variation across physicians and within physicians during the course of a shift. These findings suggest that current efforts to reduce practice variation may not affect the variation associated with physician preferences, which reflect underlying differences in patient needs and not physician practice

Overview of methods used in cross-culturalcomparisons of menopausal symptoms and their determinants: Guidelines for Strengthening the Reporting of Menopause and Aging (STROMA) studies

This paper reviews the methods used in cross-cultural studies of menopausal symptoms with the goal of formulating recommendations to facilitate comparisons of menopausal symptoms across cultures. It provides an overview of existing approaches and serves to introduce four separate reviews of vasomotor, psychological, somatic, and sexual symptoms at midlife. Building on an earlier review of cross-cultural studies of menopause covering time periods until 2004, these reviews are based on searches of Medline, PsycINFO, CINAHL and Google Scholar for English-language articles published from 2004 to 2010 using the terms “cross cultural comparison” and “menopause.” Two major criteria were used: a study had to include more than one culture, country, or ethnic group and to have asked about actual menopausal symptom experience. We found considerable variation across studies in age ranges, symptom lists, reference period for symptom recall, variables included in multivariate analyses, and the measurement of factors (e.g., menopausal status and hormonal factors, demographic, anthropometric, mental/physical health, and lifestyle measures) that influence vasomotor, psychological, somatic and sexual symptoms. Based on these reviews, we make recommendations for future research regarding age range, symptom lists, reference/recall periods, and measurement of menopausal status. Recommendations specific to the cross-cultural study of vasomotor, psychological, somatic, and sexual symptoms are found in the four reviews that follow this introduction

A Comparison of Patient History- and EKG-based Cardiac Risk Scores.

Patient-specific risk scores are used to identify individuals at elevated risk for cardiovascular disease. Typically, risk scores are based on patient habits and medical history - age, sex, race, smoking behavior, and prior vital signs and diagnoses. We explore an alternative source of information, a patient's raw electrocardiogram recording, and develop a score of patient risk for various outcomes. We compare models that predict adverse cardiac outcomes following an emergency department visit, and show that a learned representation (e.g. deep neural network) of raw EKG waveforms can improve prediction over traditional risk factors. Further, we show that a simple model based on segmented heart beats performs as well or better than a complex convolutional network recently shown to reliably automate arrhythmia detection in EKGs. We analyze a large cohort of emergency department patients and show evidence that EKG-derived scores can be more robust to patient heterogeneity